Image Steganography-based Copyright and Privacy-Protected Image Trading Systems

This paper proposes steganography-based copyright- and privacy-protected image trading systems using image transformation, i.e., either discrete cosine transform (DCT) or Hadamard transform (HT). In the systems, there are a content provider (CP), a consumer, the first trusted third party (TTP), and the second TTP. To protect the copyright of the image, the consumer ID is embedded into the amplitude components of the commercial image by the first TTP using the digital fingerprinting technique, and to protect the consumer's privacy against the first TTP and a malicious third party (s), the image steganography is applied to the commercial image by using image transformation. A color dummy image is used instead of a gray dummy image for security purposes. After applying the image transformation to both images, the coefficient signs of the commercial image are replaced by the coefficient signs of the dummy image pixel-by-pixel so that the inversely transformed commercial image looks like the dummy image instead of the commercial image. Once the consumer receives the fingerprinted image from the first TTP and the coefficient signs of the commercial image from the second TTP, the consumer reconstructs the fingerprinted commercial image without losing the hidden fingerprint at all because of the compatibility of the proposed image steganography method and the amplitude-based fingerprinting method. The experimental results confirm that the stego-images generated by the proposed systems do not look suspicious with higher qualities compared with those generated by existing systems. Moreover, the fingerprinted image quality and the correct fingerprint extracting rate have been improved by the proposed systems.